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BackgroundCarpal tunnel syndrome (CTS) and spinal canal stenosis can be frequently observed in the medical history of patients with transthyretin amyloidosis (ATTR), both in the hereditary (mt-ATTR) and wild-type (wt-ATTR) form. The aim of this retrospective single-center analysis was to determine the prevalence of these findings, delay to diagnosis of systemic amyloidosis and the prognostic value in a large cohort of patients with wt-ATTR and mt-ATTR amyloidosis.MethodsMedical records of 253 patients diagnosed with wt-ATTR, 136 patients with mt-ATTR and 77 asymptomatic gene carriers were screened for history of CTS and spinal canal stenosis and laboratory analysis, electrocardiography and echocardiographic results, respectively. Clinical follow-up was performed by phone assessment.ResultsHistory of CTS was present in 77 patients (56%) with mt-ATTR, in 152 patients (60%) with wt-ATTR and even in 10 of the asymptomatic gene carriers (13%). Latency between carpal tunnel surgery and first diagnosis of systemic amyloidosis was significantly longer in wt-ATTR compared to mt-ATTR (117 ± 179 months vs. 66 ± 73 months; p = 0.02). In total, 36 patients (14%) with wt-ATTR and 7 patients (5%) with mt-ATTR had a history of clinically significant spinal canal stenosis. In the subgroup of mt-ATTR, patients with CTS had thicker IVS (19 ± 5 mm vs. 16 ± 5 mm, p < 0.05), higher LV mass index (225 ± 78 g vs. 193 ± 98 g, p < 0.05), lower Karnofsky index (78 ± 15% vs. 83 ± 17%, p < 0.05), and lower mitral annular plane systolic excursion (MAPSE; 9 ± 4 mm vs. 11 ± 5 mm, p < 0.05) compared to patients without CTS, whereas in wt-ATTR no significant differences could be observed. No significant difference in survival was observed between patients with and without CTS (wt-ATTR: 67 vs. 63 months, p = 0.45; mt-ATTR: 74 vs. 63 months, p = 0.60). A combination of CTS and spinal stenosis was present in 32 wt-ATTR patients (12%) and 3 mt-ATTR patients (2.2%).ConclusionsThe prevalence of CTS is high and the latency between CTS surgery and diagnosis of amyloidosis is long among patients with wt-ATTR and mt-ATTR. CTS might be predictive for future occurrence of systemic (predominantly cardiac) ATTR amyloidosis.

[...]things don't go well, but it's an interesting exploration of the difference between human and machine intelligence. [...]ChatGPT has the potential to significantly impact the clinical and translational medicine fields by providing access to up-to-date information, improving patient engagement and reducing workloads for healthcare providers. [...]it would be part of GCP to train and validate the ChatGPT algorithm, for example, for diagnosis and therapy-accompanying applications on relevant, evidence-based knowledge bases, before it can be used.

Background The introduction of functional in-silico models, in addition to in-vivo tumor models, opens up new and unlimited possibilities in cancer research and drug development. The world's first digital twin of the A549 cell's electrophysiology in the human lung adenocarcinoma, unveiled in 2021, enables the investigation and evaluation of new research hypotheses about modulating the function of ion channels in the cell membrane, which are important for better understanding cancer development and progression, as well as for developing new drugs and predicting treatments. Main body The developed A549 in-silico model allows virtual simulations of the cell’s rhythmic oscillation of the membrane potential, which can trigger the transition between cell cycle phases. It is able to predict the promotion or interruption of cell cycle progression provoked by targeted activation and inactivation of ion channels, resulting in abnormal hyper- or depolarization of the membrane potential, a potential key signal for the known cancer hallmarks. For example, model simulations of blockade of transient receptor potential cation channels (TRPC6), which are highly expressed during S-G2/M transition, result in a strong hyperpolarization of the cell’s membrane potential that can suppress or bypass the depolarization required for the S-G2/M transition, allowing for possible cell cycle arrest and inhibition of mitosis. All simulated research hypotheses could be verified by experimental studies. Short conclusion Functional, non-phenomenological digital twins, ranging from single cells to cell–cell interactions to 3D tissue models, open new avenues for modern cancer research through \"dry lab\" approaches that optimally complement established in-vivo and in-vitro methods.

Computational modeling and simulation are playing an increasingly important role in oncology, bridging biological research, data science and clinical practice to better understand cancer complexity and inform therapeutic development. This special issue presents recent advances in multiscale modeling, artificial intelligence‐driven systems, digital twins, and in silico trials, illustrating the evolving potential of computational tools to support innovation from bench to bedside. Together, these contributions outline a future in which precision medicine, adaptive therapies and personalized diagnostics are guided by integrative and predictive modeling approaches.

Stereo‐cell is a newly developed platform for spatial single‐cell sequencing that integrates morphology, transcriptomics, and proteomics in high resolution. By preserving spatial context while enabling multimodal profiling, it bridges the gap between advanced omics and traditional pathology, supporting the detection of rare cells and clinically interpretable diagnoses. This letter highlights the technical innovations of Stereo‐cell, its positioning within the spatial omics landscape, and its potential for precision medicine. Important challenges in data integration, regulatory compliance, and digital modelling are discussed as essential steps on the path to clinical implementation.

Computational modeling and simulation are playing an increasingly important role in oncology, bridging biological research, data science and clinical practice to better understand cancer complexity and inform therapeutic development. This special issue presents recent advances in multiscale modeling, artificial intelligence‐driven systems, digital twins, and in silico trials, illustrating the evolving potential of computational tools to support innovation from bench to bedside. Together, these contributions outline a future in which precision medicine, adaptive therapies and personalized diagnostics are guided by integrative and predictive modelling approaches.

Nonreciprocal transport refers to charge transfer processes that are sensitive to the bias polarity. Until recently, nonreciprocal transport was studied only in dissipative systems, where the nonreciprocal quantity is the resistance. Recent experiments have, however, demonstrated nonreciprocal supercurrent leading to the observation of a supercurrent diode effect in Rashba superconductors. Here we report on a supercurrent diode effect in NbSe 2 constrictions obtained by patterning NbSe 2 flakes with both even and odd layer number. The observed rectification is a consequence of the valley-Zeeman spin-orbit interaction. We demonstrate a rectification efficiency as large as 60%, considerably larger than the efficiency of devices based on Rashba superconductors. In agreement with recent theory for superconducting transition metal dichalcogenides, we show that the effect is driven by the out-of-plane component of the magnetic field. Remarkably, we find that the effect becomes field-asymmetric in the presence of an additional in-plane field component transverse to the current direction. Supercurrent diodes offer a further degree of freedom in designing superconducting quantum electronics with the high degree of integrability offered by van der Waals materials. The supercurrent diode effect was recently observed in a Nb/V/Ta superlattice thin film with Rashba-type spin-orbit coupling. Here, the authors observe this effect in few-layer NbSe 2 crystals driven by valley-Zeeman-type spin-orbit coupling and find that the effect is proportional to out-of-plane magnetic field.

For cardiac defibrillator testing and design purposes, the range and limits of the human TTI is of high interest. Potential influencing factors regarding the electronic configurations, the electrode/tissue interface and patient characteristics were identified and analyzed. A literature survey based on 71 selected articles was used to review and assess human TTI and the influencing factors found. The human TTI extended from 12 to 212 Ω in the literature selected. Excluding outliers and pediatric measurements, the mean TTI recordings ranged from 51 to 112 Ω with an average TTI of 76.7 Ω under normal distribution. The wide range of human impedance can be attributed to 12 different influencing factors, including shock waveforms and protocols, coupling devices, electrode size and pressure, electrode position, patient age, gender, body dimensions, respiration and lung volume, blood hemoglobin saturation and different pathologies. The coupling device, electrode size and electrode pressure have the greatest influence on TTI.

Transport is non-reciprocal when not only the sign, but also the absolute value of the current depends on the polarity of the applied voltage. It requires simultaneously broken inversion and time-reversal symmetries, for example, by an interplay of spin–orbit coupling and magnetic field. Hitherto, observation of nonreciprocity was tied to resistivity, and dissipationless non-reciprocal circuit elements were elusive. Here we engineer fully superconducting non-reciprocal devices based on highly transparent Josephson junctions fabricated on InAs quantum wells. We demonstrate supercurrent rectification far below the transition temperature. By measuring Josephson inductance, we can link the non-reciprocal supercurrent to an asymmetry of the current–phase relation, and directly derive the supercurrent magnetochiral anisotropy coefficient. A semiquantitative model explains well the main features of our experimental data. Non-reciprocal Josephson junctions have the potential to become for superconducting circuits what pn junctions are for traditional electronics, enabling new non-dissipative circuit elements.Diodes exhibit non-reciprocal current–voltage relations, that is, the resistivity depends on the direction of the current flow. Now an array of Josephson junctions with large spin–orbit interaction acts as the superconducting version of a diode, where dissipation-free supercurrent flows in one direction, but not the other.

According to the MDCG 2019-11 guidance document, the gap in SaMD classification has been closed so far.8 A Product Watch Report of the European Commission from July 2020 provides an additional update on this topic, discussing AI, ML and statistical tools for risk estimation or decision support.9 The very recently published AI Act (June 2023), a proposed European law on artificial intelligence, will have far-reaching consequences on medical device regulation in Europe in the near future. The International Medical Device Regulators Forum (IMDRF)/Software as a Medical Device Working Group to harmonize the regulatory requirements published a possible risk categorization framework for SaMD in 2014, and a follow-up document with more detailed information on ML/AI-based software in 2022.10 The IMDRF and FDA recommendations allow for clearer identification of risk categories based on the ‘intended use’ for healthcare decisions in different medical situations or conditions (diagnosis, prognosis, prevention or treatment). SEE PDF] In contrast to ‘locked’ software algorithms with fixed functions, for example, a classifier for clinical decision support, an ‘adaptive, continuous learning’ (non-locked) algorithm changes its behavior. Because the standard medical device regulatory process is currently not designed for adaptive AI/ML technologies, additional efforts are needed by the regulators, although these algorithms have the potential to adapt and optimize software performance, in part in real-time, to continuously improve patient health outcomes.